Go, go agent job hunt!
An agentic AI workflow that tailors resumes and cover letters automatically
Applying for jobs shouldn’t be a full-time job.
That’s the principle behind the open-source AI Jobs Applier Agent I built and shared on GitHub.
Designed to streamline the repetitive burden of tailoring resumes and cover letters, this agent automates the grunt work, so applicants can focus on preparing for interviews instead of filling out the same form countless times.
The tool consists of several core components:
A master resume and cover letter template in plain-text format for easy parsing into YAML or JSON. The cover letter functions as a dynamic template, filled with logic and modular sections that highlight experience and skills based on the industry and role. Variants allow you to emphasize the right traits for the right opportunity.
Next comes job description extraction, where the agent automatically pulls in listings from sites like LinkedIn, BuiltIn and Indeed. It then uses Natural Language Processing (NLP) to extract keywords from the responsibilities and qualifications summaries of each listing, feeding them into the tailoring engine.
The third stage, auto-application on the job portals, uses Selenium and Robotic Process Automation (RPA) tactics to log in to Applicant Tracking Systems like Greenhouse and Workday, populate the forms each system requires, and upload your resume and cover letter. OpenAI’s API fine-tunes the resume and cover letter to the job, and Pandas help match your achievements with what each posting emphasizes.
Finally, a pipeline ties it all together: job description in, tailored documents out...with auto-apply or review-ready drafts saved to a local folder. This gives you more control over what's submitted than paid tools like Jobscan, Sonara AI, AIApply, Careerflow.ai and others.
Ethics in, ethics out
⚠️ Use responsibly
This workflow is meant to streamline applications for roles you’re genuinely qualified for. It is by no means meant for mass submitting resumes and cover letters at random.
Misusing automation and tailoring to apply en masse for jobs outside your expertise adds to the growing noise recruiters face and contributes to a system where bots screen bots, burying real talent in the process.
Tools like this should amplify credibility, not undermine it.
Below are a few representative snippets from the agent’s logic.
# Load the resume and job description
with open(resume_path, "r") as file:
resume_text = file.read()
with open(job_description_path, "r") as file:
job_description = file.read()# Choose resume style interactively
style_answer = inquirer.prompt([
inquirer.List("style", message="Select a resume style", choices=choices)
])# Generate PDF from LLM-tailored content
result_base64 = resume_facade.create_resume_pdf()
with open("resume.pdf", "wb") as f:
f.write(base64.b64decode(result_base64))Shipping yourself smarter
Getting this workflow running requires some technical setup: Python, pip, Selenium and API keys.
But the long-term savings in time and effort can be substantial.
It’s not magic. It’s product thinking applied to your job hunt, freeing you up to focus on networking and interviewing while the “paperwork” handles itself.
